Unsupervised Anomaly Detection on Microservice Traces through Graph VAE-Reference-Cited by-同舟云学术

Unsupervised Anomaly Detection on Microservice Traces through Graph VAE

Published:2023-04-30 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the ACM Web Conference 2023
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Author:

Xie Zhe¹^ORCID,Xu Haowen¹^ORCID,Chen Wenxiao¹^ORCID,Li Wanxue²^ORCID,Jiang Huai²^ORCID,Su Liangfei²^ORCID,Wang Hanzhang³^ORCID,Pei Dan¹^ORCID

Affiliation:

1. Department of Computer Science and Technology, Tsinghua University, China

2. eBay, China

3. eBay, USA

Funder

Research Council of Norway

Beijing National Research Center for Information Science and Technology

State Key Program of National Natural Science of China

National Key Research and Development Program of China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3543507.3583215

Reference34 articles.

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3. Yuri Burda , Roger B. Grosse , and Ruslan Salakhutdinov . 2016. Importance Weighted Autoencoders . In 4th International Conference on Learning Representations, ICLR 2016 , San Juan, Puerto Rico , May 2-4, 2016, Conference Track Proceedings, Yoshua Bengio and Yann LeCun (Eds .). http://arxiv.org/abs/1509.00519 Yuri Burda, Roger B. Grosse, and Ruslan Salakhutdinov. 2016. Importance Weighted Autoencoders. In 4th International Conference on Learning Representations, ICLR 2016, San Juan, Puerto Rico, May 2-4, 2016, Conference Track Proceedings, Yoshua Bengio and Yann LeCun (Eds.). http://arxiv.org/abs/1509.00519

4. Anomaly detection

5. Unsupervised Anomaly Detection for Intricate KPIs via Adversarial Training of VAE

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